The present disclosure relates generally to test systems and methods for detecting the presence of markers in animals. More specifically, the test systems and methods of the present disclosure may be used to detect a pregnancy marker that indicates if an animal, such as a ruminant, is pregnant.
Traditional testing for determining the pregnancy of some animals, such as ruminants, involves physical inspection of such an animal by a veterinarian. Traditional testing methods include using ultrasound and by rectal palpitation. However, these tests require an expert to perform the test, are time intensive, and are not cost effective.
Blood-based or other body fluid-based (i.e., milk) tests for detecting pregnancy markers provide another tool for aiding in early pregnancy diagnosis. In such tests, a sample of animal fluid can be withdrawn onsite, and then sent to an offsite laboratory for detection of a marker whose presence indicates that an animal is pregnant. For example, BioTracking LLC offers a laboratory test service for detecting the presence of a protein marker called pregnancy-specific protein B (PSPB) in ruminant animals. See U.S. Pat. Nos. 4,554,256 and 4,705,748, both of which are incorporated herein by reference. This test requires sending a blood sample taken onsite from a ruminant, such as a cow, to a laboratory, where a sandwich ELISA test is used to detect the presence of PSPB in the sample using quantitative means. PSPB includes several molecular weight and isoelectric variants of proteins. (Sasser and Ruder, 1987 & Sasser et al., 1989). Therefore, a polyclonal antiserum can be used to detect several of these protein variants of PSPB (Sasser et al., 1986). Additionally, PSPB molecules, referred to as pregnancy associated glycoproteins (PAGs), have been found in several eutherian mammals (Placentalia); most specifically they have been found in Artiodactyla, Perissodactyla, Carnivora and Rodentia (Szafranska et al., 2006).
There is not currently available a simple, non-laboratory (i.e., “on-the-farm”) test for detecting markers, such as a pregnancy marker, that a non-professional can fully administer in the field. A need exists for a test that employs qualitative or semi-qualitative metrics for detecting markers, including for detecting pregnancy markers to determine if an animal is pregnant. A non-professional could use such a test in the field instead of requiring a professional laboratory analysis. An onsite test may also improve temporal efficiency by decreasing the time from sample collection to result, potentially from several days to hours or minutes.
Moreover, testing methods designed only to render a binary determination (e.g., positive/negative; reactive/non-reactive; and/or pregnant/not-pregnant) are limited in that they produce ambiguous results under certain conditions. For example, when a pregnancy is aborted or terminates prematurely, certain pregnancy markers may still be present in the blood. Depending on the timing and method of detection used, these markers may be detected creating a false positive result (e.g., a not pregnant animal being categorized as pregnant). False positives are detrimental to reproductive management decisions as temporal efficiency is decreased (e.g., takes longer to correctly identify the pregnancy status of the animal).
When using a binary approach, a main way to improve and optimize test results is by adjusting the sensitivity and specificity of the test. For pregnancy testing, sensitivity may be the percentage of pregnant animals correctly identified as pregnant. Specificity may be the number of not pregnant animals correctly identified as not pregnant. The problem is the sensitivity and specificity for a binary classification is connected such that an improvement in one parameter can be offset by decreased performance in the other. For example, a cutoff that results in more efficient identification of not pregnant animals (improved specificity) can be offset by having more unintentional hormone induced abortions due to more false negatives (lower sensitivity). A cutoff resulting in better identification of pregnant animals (improved sensitivity) and less induced abortions can be offset by decreased efficiency for taking longer to identify a portion of not pregnant animals due to more false positives (lower specificity).
Under the binary approach, there is therefore some probability of false positives and false negatives no matter what signal is set as the binary test standard. Setting the test standard at a cutoff yielding 100% sensitivity will increase the probability of false positives. Setting the test standard cutoff to yield 100% specificity will increase the probability of false negatives. Setting a cutoff between 100% sensitivity and 100% specificity may allow for some optimization, but there will remain some probability of false positive and false negative results.
A need exists for a test that can minimize the issues associated with specificity and sensitivity for binary tests. A need exists for a pregnancy test for early identification of non-pregnant animals with limited misidentification of pregnant animals. The sooner a decision can be made following previous pregnancy and subsequent breeding, the more benefit is attained.